2 citations · 6 across the 8 of their papers we have counts for
8 papers
StyleTTS-ZS: Efficient High-Quality Zero-Shot Text-to-Speech Synthesis with Distilled Time-Varying Style Diffusion
Yinghao Aaron Li, Xilin Jiang, Cong Han +1
The rapid development of large-scale text-to-speech (TTS) models has led to significant advancements in modeling diverse speaker prosody and voices. However, these models often fac…
Style-Talker: Finetuning Audio Language Model and Style-Based Text-to-Speech Model for Fast Spoken Dialogue Generation
Yinghao Aaron Li, Xilin Jiang, Jordan Darefsky +2
The rapid advancement of large language models (LLMs) has significantly propelled the development of text-based chatbots, demonstrating their capability to engage in coherent and c…
Exploring Self-Supervised Contrastive Learning of Spatial Sound Event Representation
Xilin Jiang, Cong Han, Yinghao Aaron Li +1
In this study, we present a simple multi-channel framework for contrastive learning (MC-SimCLR) to encode 'what' and 'where' of spatial audios. MC-SimCLR learns joint spectral and…
HiFTNet: A Fast High-Quality Neural Vocoder with Harmonic-plus-Noise Filter and Inverse Short Time Fourier Transform
Yinghao Aaron Li, Cong Han, Xilin Jiang +1
Recent advancements in speech synthesis have leveraged GAN-based networks like HiFi-GAN and BigVGAN to produce high-fidelity waveforms from mel-spectrograms. However, these network…
SLMGAN: Exploiting Speech Language Model Representations for Unsupervised Zero-Shot Voice Conversion in GANs
Yinghao Aaron Li, Cong Han, Nima Mesgarani
In recent years, large-scale pre-trained speech language models (SLMs) have demonstrated remarkable advancements in various generative speech modeling applications, such as text-to…
Improved Decoding of Attentional Selection in Multi-Talker Environments with Self-Supervised Learned Speech Representation
Cong Han, Vishal Choudhari, Yinghao Aaron Li +1
Auditory attention decoding (AAD) is a technique used to identify and amplify the talker that a listener is focused on in a noisy environment. This is done by comparing the listene…